The proliferation of mobile devices is changing the way people interact. Mobile devices are also increasing in power, sophistication and features further changing the way people interact. Social networking is on application of how such interaction is evolving.
One area of evolution is matching algorithms, including ad hoc matching algorithms. The prior art indicates that most available ad hoc matching algorithms are primarily designed for infrastructure-based distributed systems and do not necessarily address the volatile and low power characteristics necessary for ad hoc networks. One example of such prior art (though it does not even address matching algorithms) is A. K. Dey, G. D. Abowd & D. Salbe, “A Conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-Aware Applications” Human-Computer Interaction, Vol. 16, No. 2, 3 & 4, pp. 97-166, 2001. (“Dey”) Dey provides a conceptual framework for building generic context aware applications. Dey introduces a context toolkit and discusses how such a toolkit can be customized for different scenarios from an intelligent tour guide to a conference assistant. By detaching the sensory networks from the applications semantics, interfaces and information aggregators are created as a middleware. Also the type of location sensors can be changed to various technologies without changing the applications logic. This provides programmers the ability to build context aware applications and customize them with relatively few modifications. However, in Dey, location is the salient context and the ability of the system to deal with more complex contexts and its scalability is not currently proven.
US Patent Publication US 2007/0008905A1 to Berger et al (“Berger”) discloses a method that clusters a plurality of users in a mobile network according to a specific profile. Data regarding the user is allocated to each user. Data is exchanged between at least two users as soon as said users are located in a predefined communication range in order to spot users with profiles having a given content. Berger does not meaningfully address how prioritization of matches is performed. Berger also does not meaningfully address the handshaking process between the nodes. While Berger suggests that the proposed clustering model is possible through both Wi-Fi and Bluetooth, these protocols have different schemes in peer-pairing (handshaking) and usually pairing happens through sharing a key. If the pairing is overridden or disabled there are security concerns. Berger also does not meaningfully describe how users access to the same search templates, suggesting that perhaps Berger intends that the solution in Berger is hardcoded to devices and does not have the customization capability. Berger also does not discuss how data is exchanged and propagated between the nodes. Propagation of messages in an ad hoc network must follow certain principles and protocols, but Berger does not refer to any standard of how such interaction may happen. Also it should be noted that in Bluetooth communications, each Master Device can only be connected to up to a limited number of devices at the same time. Berger does not discuss how scheduling is performed when the number of nodes increase. Berger furthermore does not discuss scheduling models in building and connecting the mesh networks. This means that if the offered data is not in the range of protocol's discovery range, matchmaking would not happen.
U.S. Pat. No. 6,542,749 to Tanaka et al (“Tanaka”) provides a method and system for connecting proximately located telecommunications units. The method and system may be used in a location aware telecommunications system that can determine the location of a telecommunications unit (TU) being used within the system. A user may be connected to one or more other users when they have compatible attributes and when they are located within a predetermined distance of each other. The connection may be established between TUs of two or more users, based on attribute and distance information maintained by a server computer, upon the request of an initiating user's TU.
Tanaka can be used for processing of passive information but Tanaka does not meaningfully disclose real time information processing. Tanaka, unlike Berger, also relies on a centralized framework, and relies on a preexisting communications infrastructure such as a core mobile network like a Global System for Mobile communications (GSM) network, or a Code Division Multiple Access (CDMA) network, or Universal Mobile Telecommunications Service (UMTS). Other types of core mobile network indication infrastructures will occur to those of skill in the art. Tanaka may potentially suffer from a high network latency since any point of failure in the core mobile network can impact communication throughput. Another aspect of Tanaka is that the location of mobile are determined by the telecom base stations, which can impact granularity of locations. Column 9, lines 45 through 65 of Tanaka provides general description of match-making algorithm which is used in any networking system but such an algorithm can be further expanded. Tanaka also focuses on a scoring model that is based on degrees of separations but the inventors believe there is a need for different scoring models.
U.S. Pat. No. 5,086,394 to Shapira (Shapira) provides an introduction system for participating users, includes for each user a personal device that is subject to activation by remote paging. Each user, also has a memory device that contains personal data defining the user by personal characteristics such as traits and interests, A local control unit receives the personal data from a plurality of user memory devices and using computer means compares the personal data of each user with the personal data of other users who have within the same time frame entered their personal, data into the local control unit via their respective memory devices. Pairs who are matched to standards by the computer comparison are automatically paged via their personal devices and an introduction is facilitated.
Like much of the prior art, Shapira is based on a centralized infrastructure model which means it can suffer from the same points-of-failure issues as in Tanaka. Tanaka can have somewhat limited flexibility as Shapira focuses more on a hardware/device design rather than an a software solution. Shapira is further focused on a dating scenario impeding customization for other contexts. For Shapira, data and profiles are entered into a central server prior to meeting time (Not ad hoc and spontaneous communications). Attributes are not stored on nodes/devices themselves but retrieved from the server.
Current literature survey indicates that most available ad hoc matching algorithms are primarily designed for infrastructure-based distributed systems and do not necessarily address the volatile and low power characteristics necessary for ad hoc networks. PeopleNet (in peopleNet: wireless virtual social network. In Proceedings of the 11th Annual international Conference on Mobile Computing and Networking (Cologne, Germany, Aug. 28-Sep. 2, 2005) suggests that a potentially successful social network is location, community and time specific. It provides a comparative analysis of candidate algorithms for design parameters and produce valid results. Despite the fact that the network architecture and propagation paradigms are well defined, practical aspects of network/user interactions are overlooked. PeopleNet does not take into account the multi-step authentication of communications protocols such as Bluetooth and its resulting complications in building efficient spontaneous social networks. The framework proposed in PeopleNet, also ignores the nodes' limited battery capacity by introducing an always-on power management policy.
The inventors responsible for the present specification would like to mitigate or obviate at least one of the disadvantages of the prior art.